Despite its many advantages, analysis can be difficult to master. Making mistakes can result in incorrect results that can have serious consequences. Recognizing these mistakes and avoiding them is essential in maximizing the potential of data-driven decision-making. The majority of these errors result from mistakes or misinterpretations. They can be easily corrected by setting clear goals and encourage accuracy over speed.
Another common mistake is to believe that the variable has an average distribution when it doesn’t. This can lead to models being either overor under-fitted, and thereby compromising confidence levels and prediction intervals. Additionally, it can cause leakage between the test and training set.
It is essential to select the MA technique that is compatible with your trading style. For instance, an SMA is ideal for trending markets while an EMA is more reactive (it removes the lag which occurs in the SMA by placing priority on the most recent data). Furthermore, the parameter of the MA should be carefully selected based on whether or not you are looking for the trend to be long-term or short-term (the 200 EMA is suitable for the longer timeframe).
It’s important to double-check your work prior to submitting it to be reviewed. This https://www.sharadhiinfotech.com/4-ma-analysis-worst-mistakes is particularly true when dealing with large volumes of data, since mistakes are more likely to occur. It is also possible to have a colleague or supervisor review your work to help discover any errors you may have missed.